eugtsa/tf_pytorch_singularity:latest
$ singularity pull shub://eugtsa/tf_pytorch_singularity:latest
Singularity Recipe
Bootstrap: docker
From: neurodebian:latest
%help
Container with Anaconda 3 (Conda 2019.10), tensorflow-gpu-2.0 and notebooks environment from neurodebian.
This installation is based on Python 3.7
%files
./requirements.txt /requirements.txt
%post
apt-get update
DEBIAN_FRONTEND=noninteractive apt-get -yq install \
build-essential \
wget \
unzip \
git \
libxml2-dev \
libssl-dev \
libcurl4-openssl-dev \
libgit2-dev \
libssh2-1-dev \
python3-setuptools
wget -c https://repo.anaconda.com/archive/Anaconda3-2019.10-Linux-x86_64.sh
/bin/bash Anaconda3-2019.10-Linux-x86_64.sh -bfp /usr/local
#Conda configuration of channels from .condarc file
conda config --add channels defaults
conda config --add channels conda-forge
#Install environment
conda install --file requirements.txt
Collection
- Name: eugtsa/tf_pytorch_singularity
- License: None
View on Datalad
Metrics
key | value |
---|---|
id | /containers/eugtsa-tf_pytorch_singularity-latest |
collection name | eugtsa/tf_pytorch_singularity |
branch | main |
tag | latest |
commit | a723eb78b9f14bb9562bb5cd0c4fc8104c52f20e |
version (container hash) | 31580cb0fc73f1638d004084a83bf8f35613cd6560ec4286aa6a2276592eb8a7 |
build date | 2021-04-19T06:51:22.846Z |
size (MB) | 3961.41796875 |
size (bytes) | 4153847808 |
SIF | Download URL (please use pull with shub://) |
Datalad URL | View on Datalad |
Singularity Recipe | Singularity Recipe on Datalad |
Feedback
Was this page helpful?
Glad to hear it! Please tell us how we can improve.
Sorry to hear that. Please tell us how we can improve.